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SHMT2 regulates serine metabolism to promote the progression and immunosuppression of papillary renal cell carcinoma

Recent research has demonstrated the diverse relationship between tumour metabolism and the tumour microenvironment (TME), for example, abnormal serine metabolism. This study investigated the role of serine metabolism in papillary renal cell carcinoma (pRCC) focusing on the prognostic value and regu...

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Detalles Bibliográficos
Autores principales: Kong, Weiyu, Wang, Zhongyuan, Chen, Nuoran, Mei, Yiwen, Li, Yang, Yue, Yulin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9468258/
https://www.ncbi.nlm.nih.gov/pubmed/36110969
http://dx.doi.org/10.3389/fonc.2022.914332
Descripción
Sumario:Recent research has demonstrated the diverse relationship between tumour metabolism and the tumour microenvironment (TME), for example, abnormal serine metabolism. This study investigated the role of serine metabolism in papillary renal cell carcinoma (pRCC) focusing on the prognostic value and regulatory mechanisms. Gene expression profiles and clinical data of patients with pRCC were obtained from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database. Kaplan–Meier curves were used for survival analysis and consensus clustering for tumour serine metabolic signatures extraction. Functional analysis, including the Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA), was applied to explore the biological characteristics. The gene set variation analysis (GSVA), single-sample GSEA (ssGSEA), and Estimation of Stromal and Immune cells in Malignant Tumour tissues using Expression data (ESTIMATE) methods were utilised to estimate the immune infiltration in the various subtypes. Five serine metabolic genes (SMGs) were used to classify patients with pRCC, with four clusters identified with diverse prognoses and immune features based on these survival-related SMGs. Further analysis of the best and worst clusters (B and D clusters) revealed variations in survival, clinical progression, oncogenic pathways, and TME, which included immune infiltration scores, immunosuppressive cell infiltration, and expression of immune checkpoints. In addition, SMGs, especially SHMT2, exacerbated the carcinogenesis and immunosuppressive cells in pRCC, thus promoting tumour proliferation. In conclusion, higher SHMT2 gene expression and higher serine metabolism in tumour cells are associated with poorer clinical outcomes in pRCC. SHMT2 is a potential novel target gene for targeted therapy and immunotherapy in pRCC.